Gis and fuzzy ahp based area selection for electric vehicle charging stations

D. Guler*, T. Yomralioglu

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

8 Citations (Scopus)

Abstract

Significant work is being done to protect the world and ecosystem. Innovative approaches are being explored to reduce the harm of the methods used to sustain life. Mobility is an essential issue that affects people and society in today's life. Automobiles are the most commonly used vehicle for mobility in private life and public service activities such as transportation. One of the important subjects that should be applied to environmentally sensitive methods is transportation. One of the major problems encountered today is the harmful effects of internal combustion motor vehicles. Electric vehicles are preferred because they work efficiently and with the least damaging effect on the environment. The location of electric vehicles is a complicated problem because it depends on many different factors. In this study, fuzzy analytical hierarchy process (Fuzzy AHP) as multi-criteria decision-making (MCDM) methods and geographic information systems (GIS) to manage data which can be used for the location selection of electric vehicles charging stations are researched. The study area was determined by three neighboring districts boundaries city of Istanbul in Turkey.

Original languageEnglish
Pages (from-to)315-320
Number of pages6
JournalInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Volume42
Issue number4
DOIs
Publication statusPublished - 19 Sept 2018
EventISPRS TC IV Mid-Term Symposium on 3D Spatial Information Science - The Engine of Change - Delft, Netherlands
Duration: 1 Oct 20185 Oct 2018

Bibliographical note

Publisher Copyright:
© Authors 2018.

Funding

This work was supported by Research Fund of the Istanbul Technical University. Project Number: 41095.

FundersFunder number
Istanbul Teknik Üniversitesi41095

    Keywords

    • Electric vehicle
    • Fuzzy AHP
    • GIS
    • MCDM

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